Article pubs.acs.org/Langmuir
Thermoporometry Characterization of Silica Microparticles and Nanowires Jiaxin Wu,† Han Zheng,‡ He Cheng,§ L. Zhou,∥ K. C. Leong,⊥ R. Rajagopalan,# H. P. Too,∥ and W. K. Choi*,†,‡,§ †
NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore 117456 Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583 § Advanced Materials for Micro- and Nano-Systems Programme, Singapore-MIT Alliance, National University of Singapore, Singapore 117583 ∥ Department of Biochemistry, National University of Singapore, Singapore 117597 ⊥ GLOBALFOUNDRIES Singapore Pte. Ltd, Singapore 738406 # Skolkovo Institute of Science and Technology, Moscow, The Russian Federation ‡
S Supporting Information *
ABSTRACT: We present the results of a systematic study on the porosity of silica microparticles and nanowires prepared by glancing angle deposition−metal-assisted chemical etching (GLAD-MACE) and interference lithography−metal-assisted chemical etching (IL-MACE) techniques using the thermoporometry (TPM) method. Good agreement was obtained between our TPM results and published data provided by the suppliers of silica microparticles. TPM characterization of the GLAD-MACE and IL-MACE nanowires was carried out on the basis of parameters obtained from TPM experiments on microparticles. Our nanowires showed a similar trend but lower values of the pore volume and surface area than nanowires prepared by MACE with AgNO3 solution. We attribute the enhanced bioanalysis performance of the GLAD-MACE nanowires based devices to the increased pore volume and total surface area of the nanowires.
on spinel Li4Ti5O12 nanowires10 prepared from TiO2 powder mixed with NaOH solution and MnO2 nanowires11 obtained from dissolving MnSO4 or KMnO4 in distilled water and H2SO4. The BET technique is not suitable for Si nanowires prepared by the MACE technique because the nanowires were usually relatively scarce in quantity. As far as we are aware, there is only one report on the BET characterization of Si nanowires prepared by MACE with AgNO3 as the catalyst.12 The other popular method, namely, mercury intrusion, again requires an abundant amount of sample, and high-pressure equipment is needed to measure pores smaller than 10 nm in diameter. The intrusion of mercury also renders the sample unusable after measurement. Therefore, although both methods are well established for probing the porosity of samples of or prepared from powder, they are not suitable for the determination of the porosity of Si nanowires prepared by the MACE method. Thermoporometry (TPM),13 which is based on differential scanning calorimetry (DSC), may be advantageous for measuring the porosity of nanowires or nanotubes. This method measures the pore size and shape by the difference in
I. INTRODUCTION The porous nature of nanowires and nanotubes makes them attractive candidates for catalysts,1−4 molecular adsorption or storage materials,5,6 and sensors7,8 because porosity yields increased surface area and possibly enhances surface interactions. For example, Cai et al.1 fabricated platinum nanotubes with an intrinsic enzymelike peroxidase function, and the nanotubes demonstrated a higher affinity and reaction rate with peroxides than a multitude of metallic and nonmetallic catalysts; Mutreja et al.6 reported the storage of CaP on titania nanotubes and the subsequent controllable release of CaP by nanotubes of different diameters; and Tao et al.7 demonstrated the use of Ag nanowire monolayers for surface-enhanced Raman spectroscopy. In our recent work, silica nanowires prepared by the glancing angle deposited−metal-assisted chemical etching (GLAD-MACE) technique exhibited attractive properties for the detection of biomacromolecules.9 Despite the attractive features exhibited by nanotubes and nanowires, relatively little has been reported on the characterization of the porosity of these nanostructures because of practical challenges. The popular Brunauer−Emmett−Teller (BET) measurement of the porosity of a sample by N2 adsorption is often carried out on samples in powder form in large amounts. For example, BET experiments were carried out © 2014 American Chemical Society
Received: November 15, 2013 Revised: February 12, 2014 Published: February 15, 2014 2206
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Figure 1. Scanning electron micrograph images of silica microparticles: (A) SA1, (B) SA2, (C) SA3, (D) FS2, and (E) FS3.
Table 1. Properties of Microparticles Obtained from Sigma-Aldrich (SA1, SA2, and SA3) and Fuji Sylisia (FS1, FS2, FS3, and FS4) RBET (nm) VBET (mL/g) ABET (m2/g) shape nominal particle size (μm)
SA1
SA2
SA3
FS1
FS2
FS3
FS4
4.34 0.23 461.09 irregular 75−150
6.49 0.77 475.25 sphere 40−75
15.84 0.74 270.38 irregular 35−70
2.49 0.41 660.00 sphere 75−150
6.19 0.83 536.00 sphere 75−150
10.00 1.20 257.00 sphere 75−150
14.40 1.20 229.00 sphere 75−150
phase-transition temperatures (liquid−solid transition or changes in crystal polymorphism) of materials trapped in pores versus bulk (exterior) phases. The sensitivity of the measurement depends on the choice of the filling liquid. Water, for instance, has been commonly used for TPM measurements because its large enthalpy of fusion allows for sensitive measurement with a very small amount of sample (e.g., a few milligrams13−15). This is ideal for the porosity experiments on nanowires as a result of the scarcity of sample. The other advantage of TPM is that studies with different types of liquids, such as organic and ionic liquids, can also shed light on the effect of porosity on surface interactions.15,16 As mentioned previously, we reported good performance for our nanowire-based device for bioanalysis applications.9 We suggested that the enhanced sensitivity and capacity of such a device was due to the unique porosity characteristic created by the GLAD-MACE method. Because this is a critical parameter that determines the performance of our device, a more quantitative approach is required to measure the porosity of the nanowires. We have carried out gas adsorption experiments on the GLAD-MACE nanowires and found that this technique is not suitable because a very large number of silicon wafers (10−15 pieces of 2′′ wafers) and a long sample preparation time (10 days) were required to produce the minimum number of nanowires for a single gas adsorption experiment. For this reason, we decided to carry out detailed TPM measurements on the GLAD-MACE nanowire samples. We first performed TPM experiments on commercially available silica micro-
particles and compared the results (e.g., pore diameter, total pore volume, and total pore surface area) to corresponding data supplied by the sample manufacturers. This is to ensure that correct TPM measurements and analysis of data were carried out before we examine the porosity characteristics of our GLAD-MACE nanowires. We found that only ∼15−20 mg of such a sample (prepared from five to six wafers) was sufficient for the TPM experiments, and a more efficient use of experimental time as the duration of a TPM experiment was much shorter (10 to 80 min) as compared to that of a gas adsorption experiment (4 to 6 h).
II. EXPERIMENTS The microparticles used in this work were obtained from SigmaAldrich (the SA samples) and Fuji Sylisia (the FS samples). Some scanning electron micrograph (SEM) images of the SA and FS microparticles are shown in Figure 1. The details of the shape, pore size, pore volume, total surface area, and nominal microparticle size provided by Sigma-Aldrich and Fuji Sylisia, as measured by gas adsorption or mercury intrusion, are listed in Table 1. Note that the definition of pore size refers to the size of “cavities” on the surface of silica microparticles and nanowires. Two types of nanowires, namely, the GLAD-MACE and the interference lithography-metal-assisted chemical etching (IL-MACE) nanowires, were fabricated on n-type silicon wafers with a resistivity of 8−12 Ω cm for this work. For the GLAD-MACE nanowires, gold was deposited on a silicon wafer by the GLAD technique,9,17 and the wafer was subsequently etched in an HF and H2O2 (4.6 M/0.44 M) solution for 20 min; the remaining gold was removed using a standard Au 2207
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Figure 2. (A, B) SEM images of nanowires obtained from the GLAD-MACE and Il-MACE methods, respectively. (Inset of A) High-resolution TEM image of a GLAD-MACE nanowire. etchant. Typical examples of a GLAD-MACE nanowire are shown in Figure 2A. Note that the GLAD-MACE method produces randomly distributed nanowires of ∼10−100 nm diameter, and they tend to clump (Figure 2A) together after drying from the etching solution as a result of capillary forces. The high-resolution transmission electron micrograph (HRTEM) image of the GLAD-MACE nanowires (inset of Figure 2A) shows a highly porous structure. The IL-MACE nanowires were fabricated by first patterning a photoresist (Ultra-i123) with the IL technique.18,19 Gold was then thermally evaporated onto the patterned wafer, and the wafer was then etched for 60 min in HF and H2O2 solution of the same concentrations as for the GLADMACE nanowires. The wafers were then blown dry with N2, and the remaining gold was removed. Typical IL-MACE nanowires are shown in Figure 2B. The IL-MACE nanowires are ordered and ∼200−400 nm in diameter but also clump slightly at the top after the drying process. The IL-MACE nanowires had a smoother surface as compared to the GLAD-MACE nanowires. After being oxidized in pure O2 at 900 °C for 35 min, both types of nanowires were then manually scratched off of the silicon wafers with a clean surgical blade. The gas adsorption experiments were performed with a Quantachrome NOVA 4200e surface area and pore size analyzer. The analyzer used the BET method to calculate the sample surface area and used the Barrett−Joyner−Halenda (BJH) method to estimate the pore diameter and volume. The results from the gas desorption branch were used to provide a comparison to the melting curve from TPM experiments. The samples were weighed and degassed at 120 °C for 2 h prior to N2 adsorption. A 20-point adsorption−desorption curve was taken for the microparticles from Sigma-Aldrich. The TPM measurements were performed on a Mettler Toledo DSC I with an HSS2 sensor and a heat-flow sensitivity of 0.2 μW. Deionized water (16 MΩ, Millipore Milli-Q system) was chosen as the pore-filling liquid to allow a lower sample heating rate for improved sample equilibration and peak resolution. All samples were immersed in water and placed in a vacuum for at least 2 h to remove air from pores prior to DSC measurements. Samples were flash frozen to −50 °C or less, and then melting curves were taken at heating rates of between 0.5 and 10 °C/min.
α=
(2)
where γs,l is the ice−water interfacial tension, T0 is the normal melting point of water, θ is the contact angle between water and the silica substrate (55°), ρ is the density of water, ΔH is the heat of fusion of water, and ΔT is the difference between the TPM-measured melting point and the normal melting point. It is well accepted that there exists a nonfreezable layer of water that lies between the solid ice core and the surrounding pore walls, and the thickness (δ) of this layer diminishes as the temperature decreases. The diameter of the pore, R, is the sum of the diameter of the solid core and the outer liquid layer thickness, or R=r+δ=
α +δ ΔT
(3)
Note that because the pore size affects ice crystal stacking and the interactions among water, ice, and the substrate wall, different sets of α, δ, and γs,l may exist for different pore sizes. During melting, the rate of change of the total volume of ice, Vs, normalized by the sample mass, m, is related to the heat flow dq/dt by
dq 1 dVs = dt dt mρΔH
(4)
where ρ = 917 × (1.032 − 1.17 × 10−4T )
(5)
20
is the density of ice (mg/mL) and the density of ice in pores is assumed to have the same temperature dependency as bulk ice. Because the microparticles and nanowires are all silicabased, we assume that the same surface chemistry applies to all of our samples. The size distribution of the ice core is obtained by combining eqs 1 and 4 to obtain
III. RESULTS AND DISCUSSION From the Gibbs−Dühem and Laplace equations, the radius (r) of the ice core melting in a pore is related to the melting point offset, ΔT = T − T0, by 2γ s,lT0 cos θ α = r= ρΔH ΔT ΔT
2γ s,lT0 cos θ ρΔH
dVs dV dt d(ΔT ) = s dR dt d(ΔT ) dR
(1)
(6)
and d(ΔT)/dt is equal to the heating rate because T0 is constant.
and 2208
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One must account for the thickness of the nonfreezable layer, so the actual pore size distribution is adjusted by the ratio of the total pore diameter over the ice core diameter14 dVDSC dV ⎛ r + δ ⎞ z dVs ⎛ R ⎞ z ⎜ ⎟ ⎟ = = s⎜ dR dR ⎝ r ⎠ dR ⎝ R − δ ⎠
(7)
where z is the shape factor for the presumed shape of the pores and is equal to 2 or 3 for cylindrical or spherical pores, respectively.14−16 The total surface area is derived from the Gibbs−Dühem equation as14 dAs,l 1 = s,l dVs γ
∫T
T
0
ΔS dT v
(8)
s,l
where A is the area of the ice−water interface, v is the specific volume of water, and ΔS is the water entropy of fusion, calculated with ΔS = ΔH/T assuming equilibrium and using ΔG = 0 = ΔH − TΔS. The actual total pore surface area, ADSC, is again adjusted by the thickness of the liquid layer in pores by14 ⎛ R ⎞z ADSC = As,l ⎜ ⎟ ⎝r⎠ z
dAs,l dVs ⎛⎜ R ⎞⎟ dR dVs dR ⎝ r ⎠
=
∫
=
∫ ddAV
s,l s
dVDSC dR dR
(9)
With these equations, the TPM method will fit the DSC heat curves to the BET data to derive information on the porosity (e.g., α and δ) of samples.14,15 Figure 3 shows the typical melting curves from our microparticle samples. For each curve, the rightmost peak, centered around 278−282 K for SA and FS samples, respectively, indicates the melting of excess water outside pores. The amplitude of this peak is similar between samples because it is solely dependent on the amount of excess water on samples. The other peaks at lower temperatures indicate the melting of water in spaces with smaller dimensions, including pores or other crevices created by particle packing. The amplitude of these peaks will vary with the pore volume of each sample. Figure 3 shows that for both the SA and FS samples the smaller the pores, the lower the pore peak position because a lower temperature is required to melt the water trapped in the pores, as predicted by eq 1. It should be noted that different heating rates were used to obtain melting curves of Figure 3A,B, and this resulted in the different pore peaks for samples with similar pore sizes. For example, samples SA2 and FS2 with pore sizes of 6.49 and 6.19 nm (Table 1) exhibit pore peaks at 265.6 and 268.9 K (Figure 3A,B), respectively. This difference of 3 K was a result of heating the two samples at 3 and 5 °C/min, respectively. Figure 3C shows the melting curves of sample SA2 obtained from different heating rates of 0.25 to 5 °C/min. It can be seen from this figure that increasing the heating rate resulted in a stronger heat flow signal. However, as the heating rate increases, less time is available for the system to equilibrate, and the pore and bulk peaks would not be as well resolved as compared to results obtained from a slower heating rate (Figure 3C). The tail of the pore peak would overlap with the onset of the excess water melting peak. A lower heating rate better allows the system to equilibrate and have better resolved peaks, but that would take
Figure 3. Measured heat curves for microparticles from (A) SigmaAldrich (SA series) at a heating rate of 3 °C/min and (B) from Fuji Sylisia (FS series) at a heating rate of 5 °C/min. (C) Measured heat curves of SA2 at different heating rates of 0.25, 2.5, and 5 °C/min.
substantially more experimental time and would give rise to lower heat flow and hence a weaker signal in the heating curves. The positions of excess water and pore peaks determine the melting point offset from the normal water melting point (ΔT = T − T0) which is used for the calculation of pore size distributions (PSD) for each sample (eq 1). Ishikiriyama et al.14 assigned T0 to be the onset temperature of the bulk water 2209
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melting peak for each sample and T to be the temperature at which the pore peak was minimized. This definition of ΔT was found to be the most consistent for the different heating rates, and they could use one set of α and δ to determine the pore diameters of different samples. Also, with a slow heating rate of 1 °C/min the peaks were well resolved, and they were able to determine the onset temperatures for peaks precisely. In contrast, our samples require greater heating rates to generate discernible peaks because some samples have very small pore volumes. In particular, as shown later, our GLAD-MACE and IL-MACE nanowire samples require a heating rate of at least 2 °C/min. Because the heating rate affects the position and resolution of peaks, we have chosen T and T0 to be the temperatures at which the pore and bulk melting peaks were at their minima. Note that Figure 3 also shows that the baselines of the peaks are well below 0 mW and vary between samples. This is due to the effect of different heating rates and different masses of water and silica for each sample. We have established the following procedure to remove the effects of heating rate and mass on the baselines of the measured heating curves. The total heat flow (dQ/dt) measured in a TPM experiment is the sum of three heating components dml dQ dT dT = ΔH + ml C l + msCs dt dt dt dt
A subtraction of the heats required to heat the water and ice yields the heat flow (dq/dt) of melting ice. Subsequently, dq/dt was substituted into eqs 1 to 9 to obtain the values of the average pore size (Rp), total pore surface area (ADSC), total pore volume (VDSC), and PSD (dVDSC/dR). These quantities from TPM were then fitted with the known porosity properties for the silica microparticles supplied by Sigma-Aldrich and Fuji Sylisia. Previous studies have often derived Rp and VDSC from known BET data14−16 by fitting α and δ. Note that even though γs,l appears to be an inherent property of the interacting phases with reported values for interaction in the bulk,24 we suspected that the surface areas of two samples with the same pore volumes may be different depending on the geometry of the pores. Hence, there must be a sample-dependent factor relating ADSC to VDSC, and hence we rewrite eq 8 as dAs,l 1 = dVs Em
∫T
T
0
ΔS dT v
(11)
where Em is a fitted parameter. For calculations in pores, we take into consideration the silica pore wall and the possibility of a nonfreezable layer of water in that Em is dependent on the phase transition with respect to the pore geometry and size. We expect that as pores become larger, water exhibits more bulk behavior and freezes with more ease, thus reducing the nonfreezable layer and the area of the ice−water interface. The calculated values of Rp, VDSC, and ADSC of silica microparticles are shown in Table 2. Details on the iterative procedures for the calculations can be found in Figure S1 of the Supporting Information. Generally speaking, the porosity properties (Rp, VDSC, and ADSC) are well matched to the known data supplied by Sigma-Aldrich and Fuji Sylisia. As shown in eq 2, α will change as a result of variations in γs,l (or Em), liquid density (ρ), and heat of fusion (ΔH), θ, or T0. The variations of ρ and ΔH should not change significantly in the present study. θ is the contact angle between the liquid and the silica wall, and cos θ may vary significantly because of topology changes in pores and hence the value of α. T0 varies with the heating rate because it is defined as the minimum in the bulk peak of the heating curve. Note that Ishikiriyama et al.14 defined T0 as the onset of the bulk peak because the peaks in the heating curves can be easily resolved at low heating rates. However, this is not the case with the less porous samples such the nanowires we experimented with in this work. To obtain clear peaks in the heating curves for our samples, the experiments needed to be carried out at high heating rates and thus will affect the value of α. δ is the thickness of the nonfreezable layer inside the pores. In our work, the variation of δ is small for most samples except for SA1. The large values of SA1 are possibly due to the inaccuracy in the experiment because its pore peak is very minor and it is difficult to manually identify these peaks. Figure 4A shows that for a particular sample (e.g., SA1) with a fixed ice core diameter (r) an increase in the heating rate will result in an increase in α, as discussed in the previous paragraph and predicted by eq 1. Figure 4A also shows that for a fixed heating rate, α increases as r increases (cf. results of FS1 to FS2 or SA1 to SA2). Brun et al.,13 Ishikiriyama et al.,14 and Moore et al.22 have all stated the significant effects of pore shape and size on the fitting parameters. As discussed in the previous paragraph, it is possible that the different surface roughnesses (resulting from the different pore shapes and sizes) of our
(10)
where ml and ms are the masses of molten and solid ice, respectively. The first term on the right represents the heat of melting water, and the second and third terms are the heats required to raise the temperature of the melted water or the remaining sum of the pore and bulk ice at time t. The heat capacities of liquid and solid H2O, Cl and Cs, are assumed to be similar to the heat capacities of bulk ice and water, which are as large as 2 and 4 mJ/mg/K.20 Jahnert et al.21 found a reduction of 20−30% in the heat of fusion of water trapped in pores versus that in the bulk (ice core size larger than 2 nm). This is in agreement with our assumption in this study. Given the bellshaped dQ/dt measured, it is reasonable to assume a sigmoidal baseline under each peak. Before the normal ice melting point is reached, the baseline consists of the heat attributed to a nearly unchanging mass of bulk ice and the accumulation of melted pore water. After the onset of bulk water melting, most pore water would have melted, and its mass remains roughly constant for the remainder of the measurement. The sigmoidal baseline under the bulk peak would be attributed to the accumulation of melted bulk water. The ice crystal polymorphs may coexist at the temperatures used in this study because there is only a small energy difference (30−35 J/mol) between the two likely polymorphs of ice (cubic or hexagonal).22 However, this is much smaller than the heat of fusion or heat capacity of ice, both in the range of kJ/mol. We therefore neglect the contribution of ice crystal polymorphism to the TPM baseline. We also consider the glass transition to be unlikely to occur in our TPM experiments; the calorimeter was typically held at −50 °C before the commencement of the heating cycle. The minimum initial temperature we tried was −70 °C. These are much higher than the glass-transition temperature of water at 130 K.23 The relatively long time involved in the manual delivery of the silica sample to the cooling chamber also invalidated the nanosecond cooling required for the formation of amorphous water. 2210
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z=3 z=2 z=3 z=2 z=3
116.27 1.06 0.061 15.78 (15.84) 0.86 (0.74) 271.6 (270.38)
z=2
111.9 1.54 0.061 15.69 (15.84) 0.86 (0.74) 272.58 (270.38)
z=3
The numbers in parentheses are the corresponding values from Table 1 for ease of comparison.
z=2
32.66 2.89 0.011 4.35 (4.34) 0.23 (0.23) 459.78 (461.09) α (nm K) δ (nm) Em (J/m2) Rp (nm) VDSC (mL/g) ADSC (m2/g)
Figure 4. Plots of (A) variations of α vs dT/dt and (B) δ vs R for the SA and FS microparticles.
samples give rise to different contact angles and hence resulted in different values of α (eq 1). However, smaller pores inhibit ice crystal nucleation because of more probable mismatches between the nucleating ice and the pore geometry, generating crystal stacking faults.25 Hence, water in larger pores can behave more similarly to bulk water, and the portion of nonfreezable water, δ, decreases as R increases, as shown in Figure 4B. Moore et al.22 had estimated δ in confined nanopores to be in the range of a few layers of molecules (i.e., 0.55 nm). Landry et al.26 have used a δ value of 1.12 nm to fit their data. Ishikiriyama et al.14 obtained from their silica microparticles a fitted value of δ = 2−4 monolayers of water (i.e., 0.6−1.5 nm). Therefore, we consider the δ values in Table 2 to be in good agreement with data reported in the literature. Figure 5 shows the typical calculation results of PSD for the SA samples. For samples SA1 and SA2, the PSDs are reasonably matched to those from BET. However, there appear to be two peaks for sample SA3 from the BET data, and the corresponding TPM data generated only one peak for z = 2 or 3. The double peaks in the BET data of SA3 may imply a unique property of sample SA3. In our TPM analysis, we converted the temperature axis of the measured heat flow to the pore diameter axis, and hence the TPM-generated PSD is critically affected by the accuracy of the heat flow curve. It was possible that there was more than one peak in the heat flow curve for SA3, and this peak might have been masked as a result of measuring the heat flow at a high heating rate. Therefore, for a sample with very small pore volume such as SA3, a more
a
z=2 z=3
46.13 2.28 0.011 4.34 (4.34) 0.225 (0.23) 459.79 (461.09)
87.8 1.11 0.043 6.49 (6.49) 0.77 (0.77) 475.32 (475.25)
SA2
SA3 93.76 0.88 0.040 6.48 (6.49) 0.77 (0.77) 475.26 (475.25)
45.08 1.42 0.041 2.55 (2.49) 0.42 (0.41) 659.61 (660)
FS1
57.76 1.06 0.025 2.50 (2.49) 0.41 (0.41) 659.01 (660)
87.46 2.25 0.062 6.19 (6.19) 0.83 (0.83) 535.87 (536)
FS2
101.84 1.62 0.062 6.19 (6.19) 0.83 (0.83) 535.87 (536)
Article
SA1
Table 2. Average Optimized Values of α, δ, and Em Obtained from a Calibration of the TPM to BET Data and the Calculated Values of the Pore Diameters (Rp), Total Pore Volume (VDSC), and Total Pore Surface Area (ADSC) of Silica Microparticlesa
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Figure 5. Calculation of the pore size distribution (PSD) of silica microparticles obtained from the BET and TPM experiments with z = 2 and 3, assuming cylindrical and spherical pores from the TPM data, respectively.
sophisticated data fitting procedure would be required to resolve any overlapping TPM peaks. Figure 6 shows the typical heat flow curves of the GLADMACE and IL-MACE nanowire samples. Note that the heat flow curve of sample SA2 is included in this figure for comparison. Note that a sigmoidal line connecting the initial data point or the peak onset point to the final data point of the heating curve was used to estimate the baseline of the ILMACE nanowire samples (S2 in the Supporting Information). We have performed repeated experiments to ensure the validity of our data (S3 in the Supporting Information). Because of the shallowness of such peaks, the difference between the initial or peak onset and the final data point was not great and the sigmoidal line was roughly linear. It can be seen that the GLAD-MACE sample has a weaker signal than that of SA2. The pore peak position of the GLAD-MACE sample is 267 °C, which is very close to that of sample SA2 at 268.5 °C. Note that the signal from the TPM experiment of the IL-MACE sample was so weak that the heat-flow curve looks flattened in Figure 6. Using the set of α and δ values obtained from the TPM experiments from microparticles, we carried out calculations based on eqs 1 to 9 and obtained the pore parameters for the GLAD-MACE and IL-MACE nanowire samples. Figure 7 shows plots of PSD versus Rp for the GLAD-MACE and ILMACE nanowire samples. It can be seen that the GLADMACE nanowires have a PSD mostly distributed between 5 and 15 nm with nanowires a dominating pore diameter of ∼6 to 7 nm. The PSD of the IL-MACE nanowires, however, shows a nearly flat distribution from ∼5 nm onward. This flat distribution is most likely due to the non-well-resolved heat flow data for this type of sample. Table 3 lists the values of Rp, VDSC, and ADSC obtained from the TPM data of GLAD-MACE and IL-MACE samples. First, there seems to be little difference in the values of Rp, VDSC, and ADSC for GLAD-MACE and IL-MACE nanowire samples obtained from z = 2 or 3. Note that the Rp value of the GLADMACE nanowires is in the range of 5.86 to 5.90 nm, which is close to that of samples FS2 and SA2. The ADSC and VDSC values of the GLAD-MACE wires are approximately 1 order of magnitude smaller than those of FS2 and SA2. This explains the
Figure 6. (A) Measured heat-flow curves for GLAD-MACE, ILMACE nanowire and SA2 samples. (B, C) Expanded views on the onset of the pore peaks for GLAD-MACE and IL-MACE nanowires, respectively. The peaks appear as a change in inflection point on the heat curve, and they overlap with the onset of the bulk melting peak at around 270 K.
weaker heat flow signal of the GLAD-MACE sample in Figure 6. The Rp value of the IL-MACE nanowires is 4 times that of GLAD-MACE, but the VDSC and ADSC values of the IL-MACE nanowires are more than 2 orders of magnitude smaller than FS2 and SA2. This explains the almost flattened heating curve of the IL-MACE sample in Figure 6B. We mentioned earlier in the Experiments section that the GLAD-MACE nanowires were thinner and more porous than the IL-MACE nanowires on the basis of the SEM and TEM results. Our TPM results in Table 3 confirm that the GLAD2212
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sample. There is also an ∼50-fold increase in ADSC for the GLAD-MACE sample than for the IL-MACE sample. It is encouraging to note that our TPM results of the GLADMACE and IL-MACE nanowires compare favorably with the BET results of Hochbaum et al. on porous and nonporous nanowires.12 The BET experiments of Hochbaum et al. yielded a mean surface area of 342 m2/g and a total pore volume of 0.88 cm3/g for the porous nanowires. This surface area corresponds to an equivalent area of 490 m2/g for porous silica resulting from the difference in density. The corresponding mean surface area and total pore volume of our GLAD-MACE samples are 51.24−54.30 m2/g and 0.078−0.087 mL/g, respectively. Although these numbers are in a similar range to that reported by Hochbaum et al., it probably accounts for our difficulty in performing BET experiments on our samples. The different values of pore volume and surface area obtained between the nanowires in this work and in Hochbaum et al. may be due to the different catalysts (Ag vs Au) and method used in preparing catalysts (solution based for AgNO3 and solid state for Au). However, it is interesting that the pore distribution curve of Hochbaum et al. also showed a very similar distribution to that in our Figure 7A. The surface area of the nonporous control nanowires of Hochbaum et al. is 1 order of magnitude greater than for our IL-MACE sample (c.f. 24 to 0.91−0.93 m2/g), again indicating the difficulty in carrying out TPM experiments on the IL-MACE samples. Note that the pore distribution curve of the nonporous control nanowires also showed a flattened curve. In our previous work,9 we aminated both the GLAD-MACE and IL-MACE nanowire-based devices using 3-aminopropyltriethoxysilane (APTES), and the density of the reactive amine groups was examined by direct coupling to Cy5-NHS esters. We reported that a flat Si surface (i.e., the control sample) was found to display minimal fluorescence, indicating very low Cy5NHS coupling. The IL-MACE nanowire device exhibited a 40fold increase in Cy5-NHS coupling over that of the flat Si surface. In contrast, a significantly greater amount of Cy5-NHS coupling (∼500-fold higher) compared to that for the flat Si surface was observed on GLAD-MACE nanowire device. We have estimated that for a smooth IL-MACE nanowire a 2.5-fold increase in the surface area would be expected as compared to that for the flat Si substrate. However, the 40-fold increase in the coupling efficiency of Cy5-NHS to the IL-MACE nanowire device indicates that a simple estimation based on an increase in the substrate surface area alone cannot account for the observed increase in the coupling efficiency on the IL-MACE nanowire device. Table 3 shows that the Rp of the IL-MACE sample is ∼4 times larger than that of the GLAD-MACE sample, and this difference in Rp is unlikely to account for increases of 40- to 500-fold for Cy-5-NHS coupling to the IL-MACE and GLADMACE nanowire-based devices, respectively. We have seen from our thermoporometry results in Table 3 that there is an increase of approximately ∼50-fold in the values of ADSC and VDSC of the GLAD-MACE nanowire sample over the IL-MACE nanowire sample. This is in very good agreement with our earlier report of a 1 order of magnitude increase in the Cy5NHS coupling between these two types of devices.9 Therefore, we suggest that the improved performance of the GLADMACE nanowire device is due to the increase in the total pore surface area and volume of the nanowires.
Figure 7. (A) Pore size distribution of two GLAD-MACE samples and one IL-MACE nanowire samples calculated from TPM data obtained at a heating rate of 5 °C/min. (B) Enlarged view of the IL-MACE nanowire PSD.
Table 3. Calculated Values of the Pore Diameter (Rp), Total Pore Volume (VDSC), and Total Pore Surface Area (ADSC) of GLAD-MACE and IL-MACE Nanowires GLAD-MACE Rp (nm) VDSC (mL/g) ADSC (m2/g)
IL-MACE nanowires
z=2
z=3
z=2
z=3
5.86 0.087 54.30
5.90 0.078 51.24
20.48 0.0085 0.93
23.07 0.0084 0.91
MACE nanowires have a smaller pore diameter than the ILMACE nanowires, and the number of pores per unit mass is much higher in the GLAD-MACE nanowires than in the ILMACE sample. This is in good agreement with our SEM and TEM results in that the TEM image showed a much rougher surface for the GLAD-MACE sample than for the IL-MACE 2213
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(5) Gupta, V. K.; Saleh, T. A. Sorption of pollutants by porous carbon, carbon nanotubes and fullerene - an overview. Environ. Sci. Pollut. Res. 2013, 20, 2828−2843. (6) Mutreja, I.; Kumar, D.; Boyd, A. R.; Meenan, B. J. Titania nanotube porosity controls dissolution rate of sputter deposited calcium phosphate (CaP) thin film coatings. RSC Adv. 20, 28, 11263− 11273. (7) Tao, A.; Franklin, K.; Hess, C.; Goldberger, J.; Rongrui, H.; Yugang, S.; Xia, Y.; Yang, P. Langmuir-Blodgett silver nanowire monolayers for molecular sensing using surface-enhanced Raman spectroscopy. Nano Lett. 2003, 3, 1229−1233. (8) Horvath, E.; Ribic, P. R.; Hashemi, F.; Forro, L.; Magrez, A. Dye metachromasy on titanate nanowires: sensing humidity with reversible molecular dimerization. J. Mater. Chem. 2012, 22, 8778−8784. (9) Dawood, M. K.; Zhou, L.; Zheng, H.; Cheng, H.; Wan, G.; Rajagopalan, R.; Too, H. P.; Choi, W. K. Nanostructured Si-nanowire microarrays for enhanced-performance bioanalytics. Lab Chip 2012, 12, 5016−5024. (10) Kim, J. K.; Cho, J. Spinel Li4Ti5O12 nanowires for high-rate Liion intercalation electrode. Electrochem. Solid-State Lett. 2007, 10, A81−A84. (11) Ranjusha, A.; Nair, S.; Ramakrishna, S.; Anjali, P.; Sujith, K.; Subramanian, K. R.V.; Sivakumar, N.; Kim, T. N.; Nair, S.r V.; Balakrishnana, A. Ultra fine MnO2 nanowire based high performance thin film rechargeable electrodes: effect of surface morphology, electrolytes and concentrations. J. Mater. Chem. 2012, 22, 20465− 20471. (12) Hochbaum, A. I.; Gargas, D.; Hwang, Y. J.; Yang, P. Single crystalline mesoporous silicon nanowires. Nano Lett. 2009, 9, 3550− 3554. (13) Brun, M.; Lallemand, A.; Quinson, J.-F.; Eyraud, C. A new method for the simultaneous determination of the size and shape of pores: the thermoporometry. Thermochim. Acta 1977, 21, 59−88. (14) Ishikiriyama, K.; Todoki, M.; Motomura, K. Pore size distribution (PSD) measurements of silica gels by means of differential scanning calorimetry. J. Colloid Interface Sci. 1995, 171, 92−102. (15) Quinson, J. F.; Astier, M.; Brun, M. Determination of surface areas by thermoporometry. Appl. Catal. 1987, 30, 123−130. (16) Riikonen, J.; Salonen, J.; Lehto, V.-P. Utilising thermoporometry to obtain new insights into nanostructured materials. J. Therm. Anal. Calorim. 2011, 105, 823−830. (17) Dawood, M. K.; Zheng, H.; Liew, T. H.; Leong, K. C.; Foo, Y. L.; Rajagopalan, R.; Khan, S. A.; Choi, W. K. Mimicking both petal and lotus effects on a single silicon substrate by tuning the wettability of nanostructured surfaces. Langmuir 2011, 27, 4126−4133. (18) Choi, W. K.; Liew, T. H.; Dawood, M. K.; Smith, H. I.; Thompson, C. V.; Hong, M. H. Synthesis of silicon nanowires and nanofin arrays using interference lithography and catalytic etching. Nano Lett. 2008, 8, 3799−3802. (19) de Boor, J.; Geyer, N.; Wittemann, J. V.; Gosele, U.; Schmidt, V. Sub-100 nm silicon nanowires by laser interference lithography and metal-assisted etching. Nanotechnology 2010, 21, 095302−1−095302− 5. (20) Fukusako, S. Thermophysical properties of ice, snow, and sea ice. Int. J. Thermophys. 1990, 11, 353−372. (21) Jähnert, S.; Vaca Chávez, F.; Schaumann, G. E.; Schreiber, A.; Schönhoff, M.; Findenegg, G. H. Melting and freezing of water in cylindrical silica nanopores. Phys. Chem. Chem. Phys. 2008, 10, 6039− 6051. (22) Moore, E. B.; de la Llave, E.; Welke, K.; Scherlis, D. A.; Molinero, V. Freezing, melting and structure of ice in a hydrophilic nanopore. Phys. Chem. Chem. Phys. 2010, 12, 4124−4134. (23) Angell, C. A. Amorphous water. Annu. Rev. Phys. Chem. 2004, 55, 559−583. (24) Faivre, C.; Bellet, D.; Dolino, G. Phase transitions of fluids confined in porous silicon: a differential calorimetry investigation. Eur. Phys. J. B 1999, 7, 19−36.
IV. CONCLUSIONS We reported the results of a systematic study of the porosity of microparticles and nanowires prepared by the GLAD-MACE and IL-MACE techniques using the TPM method. We demonstrated good agreement between our TPM-derived parameters and that provided by the manufacturers of microparticles. The α and δ values obtained from the TPM experiments of microparticles were then used for the TPM characterization of GLAD-MACE and IL-MACE nanowires. We found that the increase in the total pore volume and total surface area of the GLAD-MACE nanowires was the most likely reason for the enhanced bioanalytical performance of such a device.
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ASSOCIATED CONTENT
S Supporting Information *
Description of the iteration processes used to derive and fit parameters for thermoporometry data. This material is available free of charge via the Internet at http://pubs.acs.org.
■
AUTHOR INFORMATION
Corresponding Author
*E-mail: [email protected]. Author Contributions
J.W. and H.Z. contributed equally to this work. Author Contributions
The manuscript was written through the contributions of all authors. All authors have given approval to the final version of the manuscript. Notes
The authors declare no competing financial interests.
■
ACKNOWLEDGMENTS This work was supported by a grant from the Singapore-MIT Alliance and a Proof-of-Concept grant (R-263-000-047-001) from the National Research Foundation. We acknowledge Fuji Sylisia (Japan) for supplying the silica microspheres without charges. We also thank Professor Lee Jim Yang of the Department of Chemical and Biomolecular Engineering of NUS for useful discussions of our TPM results. J.W. thanks the NUS Graduate School for Integrative Sciences and Engineering for the provision of a research scholarship, H.Z. acknowledges the GLOBALFOUNDRIES Singapore Pte. Ltd and the Economic Development Board (EDB) of Singapore for providing a research scholarship, and H.C. acknowledges the Singapore-MIT Alliance for the provision of a research scholarship.
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REFERENCES
(1) Cai, K.; Lv, Z.; Chen, K.; Huang, L.; Wang, J.; Shao, F.; Wang, Y.; Han, H. Aqueous synthesis of porous platinum nanotubes at room temperature and their intrinsic peroxidase-like activity. Chem. Commun. 2013, 49, 6024−6026. (2) Liao, H.; Hou, Y. Liquid-phase templateless synthesis of Pt-onPd0.85Bi0.15 nanowires and PtPdBi porous nanoparticles with superior electrocatalytic activity. Chem. Mater. 2013, 25, 457−465. (3) Moutanabbir, O.; Isheim, D.; Blumtritt, H.; Senz, S.; Pippel, E.; Seidman, D. N. Colossal injection of catalyst atoms into silicon nanowires. Nature 2013, 496, 78−82. (4) Qiao, Y.; Li, C. M. Nanostructured catalysts in fuel cells. J. Mater. Chem. 2011, 21, 4027−4036. 2214
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(25) Hardy, S. C. A grain boundary groove measurement of the surface tension between ice and water. Philos. Mag. 1976, 35, 471− 484. (26) Landry, M. R. Thermoporometry by differential scanning calorimetry: experimental considerations and applications. Thermochim. Acta 2005, 433, 27−50.
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Thermoporometry Characterization of Silica Microparticles and Nanowires Jiaxin Wu,† Han Zheng,‡ He Cheng,§ L. Zhou,∥ K. C. Leong,⊥ R. Rajagopalan,# H. P. Too,∥ and W. K. Choi*,†,‡,§ †
NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore 117456 Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583 § Advanced Materials for Micro- and Nano-Systems Programme, Singapore-MIT Alliance, National University of Singapore, Singapore 117583 ∥ Department of Biochemistry, National University of Singapore, Singapore 117597 ⊥ GLOBALFOUNDRIES Singapore Pte. Ltd, Singapore 738406 # Skolkovo Institute of Science and Technology, Moscow, The Russian Federation ‡
S Supporting Information *
ABSTRACT: We present the results of a systematic study on the porosity of silica microparticles and nanowires prepared by glancing angle deposition−metal-assisted chemical etching (GLAD-MACE) and interference lithography−metal-assisted chemical etching (IL-MACE) techniques using the thermoporometry (TPM) method. Good agreement was obtained between our TPM results and published data provided by the suppliers of silica microparticles. TPM characterization of the GLAD-MACE and IL-MACE nanowires was carried out on the basis of parameters obtained from TPM experiments on microparticles. Our nanowires showed a similar trend but lower values of the pore volume and surface area than nanowires prepared by MACE with AgNO3 solution. We attribute the enhanced bioanalysis performance of the GLAD-MACE nanowires based devices to the increased pore volume and total surface area of the nanowires.
on spinel Li4Ti5O12 nanowires10 prepared from TiO2 powder mixed with NaOH solution and MnO2 nanowires11 obtained from dissolving MnSO4 or KMnO4 in distilled water and H2SO4. The BET technique is not suitable for Si nanowires prepared by the MACE technique because the nanowires were usually relatively scarce in quantity. As far as we are aware, there is only one report on the BET characterization of Si nanowires prepared by MACE with AgNO3 as the catalyst.12 The other popular method, namely, mercury intrusion, again requires an abundant amount of sample, and high-pressure equipment is needed to measure pores smaller than 10 nm in diameter. The intrusion of mercury also renders the sample unusable after measurement. Therefore, although both methods are well established for probing the porosity of samples of or prepared from powder, they are not suitable for the determination of the porosity of Si nanowires prepared by the MACE method. Thermoporometry (TPM),13 which is based on differential scanning calorimetry (DSC), may be advantageous for measuring the porosity of nanowires or nanotubes. This method measures the pore size and shape by the difference in
I. INTRODUCTION The porous nature of nanowires and nanotubes makes them attractive candidates for catalysts,1−4 molecular adsorption or storage materials,5,6 and sensors7,8 because porosity yields increased surface area and possibly enhances surface interactions. For example, Cai et al.1 fabricated platinum nanotubes with an intrinsic enzymelike peroxidase function, and the nanotubes demonstrated a higher affinity and reaction rate with peroxides than a multitude of metallic and nonmetallic catalysts; Mutreja et al.6 reported the storage of CaP on titania nanotubes and the subsequent controllable release of CaP by nanotubes of different diameters; and Tao et al.7 demonstrated the use of Ag nanowire monolayers for surface-enhanced Raman spectroscopy. In our recent work, silica nanowires prepared by the glancing angle deposited−metal-assisted chemical etching (GLAD-MACE) technique exhibited attractive properties for the detection of biomacromolecules.9 Despite the attractive features exhibited by nanotubes and nanowires, relatively little has been reported on the characterization of the porosity of these nanostructures because of practical challenges. The popular Brunauer−Emmett−Teller (BET) measurement of the porosity of a sample by N2 adsorption is often carried out on samples in powder form in large amounts. For example, BET experiments were carried out © 2014 American Chemical Society
Received: November 15, 2013 Revised: February 12, 2014 Published: February 15, 2014 2206
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Figure 1. Scanning electron micrograph images of silica microparticles: (A) SA1, (B) SA2, (C) SA3, (D) FS2, and (E) FS3.
Table 1. Properties of Microparticles Obtained from Sigma-Aldrich (SA1, SA2, and SA3) and Fuji Sylisia (FS1, FS2, FS3, and FS4) RBET (nm) VBET (mL/g) ABET (m2/g) shape nominal particle size (μm)
SA1
SA2
SA3
FS1
FS2
FS3
FS4
4.34 0.23 461.09 irregular 75−150
6.49 0.77 475.25 sphere 40−75
15.84 0.74 270.38 irregular 35−70
2.49 0.41 660.00 sphere 75−150
6.19 0.83 536.00 sphere 75−150
10.00 1.20 257.00 sphere 75−150
14.40 1.20 229.00 sphere 75−150
phase-transition temperatures (liquid−solid transition or changes in crystal polymorphism) of materials trapped in pores versus bulk (exterior) phases. The sensitivity of the measurement depends on the choice of the filling liquid. Water, for instance, has been commonly used for TPM measurements because its large enthalpy of fusion allows for sensitive measurement with a very small amount of sample (e.g., a few milligrams13−15). This is ideal for the porosity experiments on nanowires as a result of the scarcity of sample. The other advantage of TPM is that studies with different types of liquids, such as organic and ionic liquids, can also shed light on the effect of porosity on surface interactions.15,16 As mentioned previously, we reported good performance for our nanowire-based device for bioanalysis applications.9 We suggested that the enhanced sensitivity and capacity of such a device was due to the unique porosity characteristic created by the GLAD-MACE method. Because this is a critical parameter that determines the performance of our device, a more quantitative approach is required to measure the porosity of the nanowires. We have carried out gas adsorption experiments on the GLAD-MACE nanowires and found that this technique is not suitable because a very large number of silicon wafers (10−15 pieces of 2′′ wafers) and a long sample preparation time (10 days) were required to produce the minimum number of nanowires for a single gas adsorption experiment. For this reason, we decided to carry out detailed TPM measurements on the GLAD-MACE nanowire samples. We first performed TPM experiments on commercially available silica micro-
particles and compared the results (e.g., pore diameter, total pore volume, and total pore surface area) to corresponding data supplied by the sample manufacturers. This is to ensure that correct TPM measurements and analysis of data were carried out before we examine the porosity characteristics of our GLAD-MACE nanowires. We found that only ∼15−20 mg of such a sample (prepared from five to six wafers) was sufficient for the TPM experiments, and a more efficient use of experimental time as the duration of a TPM experiment was much shorter (10 to 80 min) as compared to that of a gas adsorption experiment (4 to 6 h).
II. EXPERIMENTS The microparticles used in this work were obtained from SigmaAldrich (the SA samples) and Fuji Sylisia (the FS samples). Some scanning electron micrograph (SEM) images of the SA and FS microparticles are shown in Figure 1. The details of the shape, pore size, pore volume, total surface area, and nominal microparticle size provided by Sigma-Aldrich and Fuji Sylisia, as measured by gas adsorption or mercury intrusion, are listed in Table 1. Note that the definition of pore size refers to the size of “cavities” on the surface of silica microparticles and nanowires. Two types of nanowires, namely, the GLAD-MACE and the interference lithography-metal-assisted chemical etching (IL-MACE) nanowires, were fabricated on n-type silicon wafers with a resistivity of 8−12 Ω cm for this work. For the GLAD-MACE nanowires, gold was deposited on a silicon wafer by the GLAD technique,9,17 and the wafer was subsequently etched in an HF and H2O2 (4.6 M/0.44 M) solution for 20 min; the remaining gold was removed using a standard Au 2207
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Figure 2. (A, B) SEM images of nanowires obtained from the GLAD-MACE and Il-MACE methods, respectively. (Inset of A) High-resolution TEM image of a GLAD-MACE nanowire. etchant. Typical examples of a GLAD-MACE nanowire are shown in Figure 2A. Note that the GLAD-MACE method produces randomly distributed nanowires of ∼10−100 nm diameter, and they tend to clump (Figure 2A) together after drying from the etching solution as a result of capillary forces. The high-resolution transmission electron micrograph (HRTEM) image of the GLAD-MACE nanowires (inset of Figure 2A) shows a highly porous structure. The IL-MACE nanowires were fabricated by first patterning a photoresist (Ultra-i123) with the IL technique.18,19 Gold was then thermally evaporated onto the patterned wafer, and the wafer was then etched for 60 min in HF and H2O2 solution of the same concentrations as for the GLADMACE nanowires. The wafers were then blown dry with N2, and the remaining gold was removed. Typical IL-MACE nanowires are shown in Figure 2B. The IL-MACE nanowires are ordered and ∼200−400 nm in diameter but also clump slightly at the top after the drying process. The IL-MACE nanowires had a smoother surface as compared to the GLAD-MACE nanowires. After being oxidized in pure O2 at 900 °C for 35 min, both types of nanowires were then manually scratched off of the silicon wafers with a clean surgical blade. The gas adsorption experiments were performed with a Quantachrome NOVA 4200e surface area and pore size analyzer. The analyzer used the BET method to calculate the sample surface area and used the Barrett−Joyner−Halenda (BJH) method to estimate the pore diameter and volume. The results from the gas desorption branch were used to provide a comparison to the melting curve from TPM experiments. The samples were weighed and degassed at 120 °C for 2 h prior to N2 adsorption. A 20-point adsorption−desorption curve was taken for the microparticles from Sigma-Aldrich. The TPM measurements were performed on a Mettler Toledo DSC I with an HSS2 sensor and a heat-flow sensitivity of 0.2 μW. Deionized water (16 MΩ, Millipore Milli-Q system) was chosen as the pore-filling liquid to allow a lower sample heating rate for improved sample equilibration and peak resolution. All samples were immersed in water and placed in a vacuum for at least 2 h to remove air from pores prior to DSC measurements. Samples were flash frozen to −50 °C or less, and then melting curves were taken at heating rates of between 0.5 and 10 °C/min.
α=
(2)
where γs,l is the ice−water interfacial tension, T0 is the normal melting point of water, θ is the contact angle between water and the silica substrate (55°), ρ is the density of water, ΔH is the heat of fusion of water, and ΔT is the difference between the TPM-measured melting point and the normal melting point. It is well accepted that there exists a nonfreezable layer of water that lies between the solid ice core and the surrounding pore walls, and the thickness (δ) of this layer diminishes as the temperature decreases. The diameter of the pore, R, is the sum of the diameter of the solid core and the outer liquid layer thickness, or R=r+δ=
α +δ ΔT
(3)
Note that because the pore size affects ice crystal stacking and the interactions among water, ice, and the substrate wall, different sets of α, δ, and γs,l may exist for different pore sizes. During melting, the rate of change of the total volume of ice, Vs, normalized by the sample mass, m, is related to the heat flow dq/dt by
dq 1 dVs = dt dt mρΔH
(4)
where ρ = 917 × (1.032 − 1.17 × 10−4T )
(5)
20
is the density of ice (mg/mL) and the density of ice in pores is assumed to have the same temperature dependency as bulk ice. Because the microparticles and nanowires are all silicabased, we assume that the same surface chemistry applies to all of our samples. The size distribution of the ice core is obtained by combining eqs 1 and 4 to obtain
III. RESULTS AND DISCUSSION From the Gibbs−Dühem and Laplace equations, the radius (r) of the ice core melting in a pore is related to the melting point offset, ΔT = T − T0, by 2γ s,lT0 cos θ α = r= ρΔH ΔT ΔT
2γ s,lT0 cos θ ρΔH
dVs dV dt d(ΔT ) = s dR dt d(ΔT ) dR
(1)
(6)
and d(ΔT)/dt is equal to the heating rate because T0 is constant.
and 2208
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One must account for the thickness of the nonfreezable layer, so the actual pore size distribution is adjusted by the ratio of the total pore diameter over the ice core diameter14 dVDSC dV ⎛ r + δ ⎞ z dVs ⎛ R ⎞ z ⎜ ⎟ ⎟ = = s⎜ dR dR ⎝ r ⎠ dR ⎝ R − δ ⎠
(7)
where z is the shape factor for the presumed shape of the pores and is equal to 2 or 3 for cylindrical or spherical pores, respectively.14−16 The total surface area is derived from the Gibbs−Dühem equation as14 dAs,l 1 = s,l dVs γ
∫T
T
0
ΔS dT v
(8)
s,l
where A is the area of the ice−water interface, v is the specific volume of water, and ΔS is the water entropy of fusion, calculated with ΔS = ΔH/T assuming equilibrium and using ΔG = 0 = ΔH − TΔS. The actual total pore surface area, ADSC, is again adjusted by the thickness of the liquid layer in pores by14 ⎛ R ⎞z ADSC = As,l ⎜ ⎟ ⎝r⎠ z
dAs,l dVs ⎛⎜ R ⎞⎟ dR dVs dR ⎝ r ⎠
=
∫
=
∫ ddAV
s,l s
dVDSC dR dR
(9)
With these equations, the TPM method will fit the DSC heat curves to the BET data to derive information on the porosity (e.g., α and δ) of samples.14,15 Figure 3 shows the typical melting curves from our microparticle samples. For each curve, the rightmost peak, centered around 278−282 K for SA and FS samples, respectively, indicates the melting of excess water outside pores. The amplitude of this peak is similar between samples because it is solely dependent on the amount of excess water on samples. The other peaks at lower temperatures indicate the melting of water in spaces with smaller dimensions, including pores or other crevices created by particle packing. The amplitude of these peaks will vary with the pore volume of each sample. Figure 3 shows that for both the SA and FS samples the smaller the pores, the lower the pore peak position because a lower temperature is required to melt the water trapped in the pores, as predicted by eq 1. It should be noted that different heating rates were used to obtain melting curves of Figure 3A,B, and this resulted in the different pore peaks for samples with similar pore sizes. For example, samples SA2 and FS2 with pore sizes of 6.49 and 6.19 nm (Table 1) exhibit pore peaks at 265.6 and 268.9 K (Figure 3A,B), respectively. This difference of 3 K was a result of heating the two samples at 3 and 5 °C/min, respectively. Figure 3C shows the melting curves of sample SA2 obtained from different heating rates of 0.25 to 5 °C/min. It can be seen from this figure that increasing the heating rate resulted in a stronger heat flow signal. However, as the heating rate increases, less time is available for the system to equilibrate, and the pore and bulk peaks would not be as well resolved as compared to results obtained from a slower heating rate (Figure 3C). The tail of the pore peak would overlap with the onset of the excess water melting peak. A lower heating rate better allows the system to equilibrate and have better resolved peaks, but that would take
Figure 3. Measured heat curves for microparticles from (A) SigmaAldrich (SA series) at a heating rate of 3 °C/min and (B) from Fuji Sylisia (FS series) at a heating rate of 5 °C/min. (C) Measured heat curves of SA2 at different heating rates of 0.25, 2.5, and 5 °C/min.
substantially more experimental time and would give rise to lower heat flow and hence a weaker signal in the heating curves. The positions of excess water and pore peaks determine the melting point offset from the normal water melting point (ΔT = T − T0) which is used for the calculation of pore size distributions (PSD) for each sample (eq 1). Ishikiriyama et al.14 assigned T0 to be the onset temperature of the bulk water 2209
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melting peak for each sample and T to be the temperature at which the pore peak was minimized. This definition of ΔT was found to be the most consistent for the different heating rates, and they could use one set of α and δ to determine the pore diameters of different samples. Also, with a slow heating rate of 1 °C/min the peaks were well resolved, and they were able to determine the onset temperatures for peaks precisely. In contrast, our samples require greater heating rates to generate discernible peaks because some samples have very small pore volumes. In particular, as shown later, our GLAD-MACE and IL-MACE nanowire samples require a heating rate of at least 2 °C/min. Because the heating rate affects the position and resolution of peaks, we have chosen T and T0 to be the temperatures at which the pore and bulk melting peaks were at their minima. Note that Figure 3 also shows that the baselines of the peaks are well below 0 mW and vary between samples. This is due to the effect of different heating rates and different masses of water and silica for each sample. We have established the following procedure to remove the effects of heating rate and mass on the baselines of the measured heating curves. The total heat flow (dQ/dt) measured in a TPM experiment is the sum of three heating components dml dQ dT dT = ΔH + ml C l + msCs dt dt dt dt
A subtraction of the heats required to heat the water and ice yields the heat flow (dq/dt) of melting ice. Subsequently, dq/dt was substituted into eqs 1 to 9 to obtain the values of the average pore size (Rp), total pore surface area (ADSC), total pore volume (VDSC), and PSD (dVDSC/dR). These quantities from TPM were then fitted with the known porosity properties for the silica microparticles supplied by Sigma-Aldrich and Fuji Sylisia. Previous studies have often derived Rp and VDSC from known BET data14−16 by fitting α and δ. Note that even though γs,l appears to be an inherent property of the interacting phases with reported values for interaction in the bulk,24 we suspected that the surface areas of two samples with the same pore volumes may be different depending on the geometry of the pores. Hence, there must be a sample-dependent factor relating ADSC to VDSC, and hence we rewrite eq 8 as dAs,l 1 = dVs Em
∫T
T
0
ΔS dT v
(11)
where Em is a fitted parameter. For calculations in pores, we take into consideration the silica pore wall and the possibility of a nonfreezable layer of water in that Em is dependent on the phase transition with respect to the pore geometry and size. We expect that as pores become larger, water exhibits more bulk behavior and freezes with more ease, thus reducing the nonfreezable layer and the area of the ice−water interface. The calculated values of Rp, VDSC, and ADSC of silica microparticles are shown in Table 2. Details on the iterative procedures for the calculations can be found in Figure S1 of the Supporting Information. Generally speaking, the porosity properties (Rp, VDSC, and ADSC) are well matched to the known data supplied by Sigma-Aldrich and Fuji Sylisia. As shown in eq 2, α will change as a result of variations in γs,l (or Em), liquid density (ρ), and heat of fusion (ΔH), θ, or T0. The variations of ρ and ΔH should not change significantly in the present study. θ is the contact angle between the liquid and the silica wall, and cos θ may vary significantly because of topology changes in pores and hence the value of α. T0 varies with the heating rate because it is defined as the minimum in the bulk peak of the heating curve. Note that Ishikiriyama et al.14 defined T0 as the onset of the bulk peak because the peaks in the heating curves can be easily resolved at low heating rates. However, this is not the case with the less porous samples such the nanowires we experimented with in this work. To obtain clear peaks in the heating curves for our samples, the experiments needed to be carried out at high heating rates and thus will affect the value of α. δ is the thickness of the nonfreezable layer inside the pores. In our work, the variation of δ is small for most samples except for SA1. The large values of SA1 are possibly due to the inaccuracy in the experiment because its pore peak is very minor and it is difficult to manually identify these peaks. Figure 4A shows that for a particular sample (e.g., SA1) with a fixed ice core diameter (r) an increase in the heating rate will result in an increase in α, as discussed in the previous paragraph and predicted by eq 1. Figure 4A also shows that for a fixed heating rate, α increases as r increases (cf. results of FS1 to FS2 or SA1 to SA2). Brun et al.,13 Ishikiriyama et al.,14 and Moore et al.22 have all stated the significant effects of pore shape and size on the fitting parameters. As discussed in the previous paragraph, it is possible that the different surface roughnesses (resulting from the different pore shapes and sizes) of our
(10)
where ml and ms are the masses of molten and solid ice, respectively. The first term on the right represents the heat of melting water, and the second and third terms are the heats required to raise the temperature of the melted water or the remaining sum of the pore and bulk ice at time t. The heat capacities of liquid and solid H2O, Cl and Cs, are assumed to be similar to the heat capacities of bulk ice and water, which are as large as 2 and 4 mJ/mg/K.20 Jahnert et al.21 found a reduction of 20−30% in the heat of fusion of water trapped in pores versus that in the bulk (ice core size larger than 2 nm). This is in agreement with our assumption in this study. Given the bellshaped dQ/dt measured, it is reasonable to assume a sigmoidal baseline under each peak. Before the normal ice melting point is reached, the baseline consists of the heat attributed to a nearly unchanging mass of bulk ice and the accumulation of melted pore water. After the onset of bulk water melting, most pore water would have melted, and its mass remains roughly constant for the remainder of the measurement. The sigmoidal baseline under the bulk peak would be attributed to the accumulation of melted bulk water. The ice crystal polymorphs may coexist at the temperatures used in this study because there is only a small energy difference (30−35 J/mol) between the two likely polymorphs of ice (cubic or hexagonal).22 However, this is much smaller than the heat of fusion or heat capacity of ice, both in the range of kJ/mol. We therefore neglect the contribution of ice crystal polymorphism to the TPM baseline. We also consider the glass transition to be unlikely to occur in our TPM experiments; the calorimeter was typically held at −50 °C before the commencement of the heating cycle. The minimum initial temperature we tried was −70 °C. These are much higher than the glass-transition temperature of water at 130 K.23 The relatively long time involved in the manual delivery of the silica sample to the cooling chamber also invalidated the nanosecond cooling required for the formation of amorphous water. 2210
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z=3 z=2 z=3 z=2 z=3
116.27 1.06 0.061 15.78 (15.84) 0.86 (0.74) 271.6 (270.38)
z=2
111.9 1.54 0.061 15.69 (15.84) 0.86 (0.74) 272.58 (270.38)
z=3
The numbers in parentheses are the corresponding values from Table 1 for ease of comparison.
z=2
32.66 2.89 0.011 4.35 (4.34) 0.23 (0.23) 459.78 (461.09) α (nm K) δ (nm) Em (J/m2) Rp (nm) VDSC (mL/g) ADSC (m2/g)
Figure 4. Plots of (A) variations of α vs dT/dt and (B) δ vs R for the SA and FS microparticles.
samples give rise to different contact angles and hence resulted in different values of α (eq 1). However, smaller pores inhibit ice crystal nucleation because of more probable mismatches between the nucleating ice and the pore geometry, generating crystal stacking faults.25 Hence, water in larger pores can behave more similarly to bulk water, and the portion of nonfreezable water, δ, decreases as R increases, as shown in Figure 4B. Moore et al.22 had estimated δ in confined nanopores to be in the range of a few layers of molecules (i.e., 0.55 nm). Landry et al.26 have used a δ value of 1.12 nm to fit their data. Ishikiriyama et al.14 obtained from their silica microparticles a fitted value of δ = 2−4 monolayers of water (i.e., 0.6−1.5 nm). Therefore, we consider the δ values in Table 2 to be in good agreement with data reported in the literature. Figure 5 shows the typical calculation results of PSD for the SA samples. For samples SA1 and SA2, the PSDs are reasonably matched to those from BET. However, there appear to be two peaks for sample SA3 from the BET data, and the corresponding TPM data generated only one peak for z = 2 or 3. The double peaks in the BET data of SA3 may imply a unique property of sample SA3. In our TPM analysis, we converted the temperature axis of the measured heat flow to the pore diameter axis, and hence the TPM-generated PSD is critically affected by the accuracy of the heat flow curve. It was possible that there was more than one peak in the heat flow curve for SA3, and this peak might have been masked as a result of measuring the heat flow at a high heating rate. Therefore, for a sample with very small pore volume such as SA3, a more
a
z=2 z=3
46.13 2.28 0.011 4.34 (4.34) 0.225 (0.23) 459.79 (461.09)
87.8 1.11 0.043 6.49 (6.49) 0.77 (0.77) 475.32 (475.25)
SA2
SA3 93.76 0.88 0.040 6.48 (6.49) 0.77 (0.77) 475.26 (475.25)
45.08 1.42 0.041 2.55 (2.49) 0.42 (0.41) 659.61 (660)
FS1
57.76 1.06 0.025 2.50 (2.49) 0.41 (0.41) 659.01 (660)
87.46 2.25 0.062 6.19 (6.19) 0.83 (0.83) 535.87 (536)
FS2
101.84 1.62 0.062 6.19 (6.19) 0.83 (0.83) 535.87 (536)
Article
SA1
Table 2. Average Optimized Values of α, δ, and Em Obtained from a Calibration of the TPM to BET Data and the Calculated Values of the Pore Diameters (Rp), Total Pore Volume (VDSC), and Total Pore Surface Area (ADSC) of Silica Microparticlesa
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Figure 5. Calculation of the pore size distribution (PSD) of silica microparticles obtained from the BET and TPM experiments with z = 2 and 3, assuming cylindrical and spherical pores from the TPM data, respectively.
sophisticated data fitting procedure would be required to resolve any overlapping TPM peaks. Figure 6 shows the typical heat flow curves of the GLADMACE and IL-MACE nanowire samples. Note that the heat flow curve of sample SA2 is included in this figure for comparison. Note that a sigmoidal line connecting the initial data point or the peak onset point to the final data point of the heating curve was used to estimate the baseline of the ILMACE nanowire samples (S2 in the Supporting Information). We have performed repeated experiments to ensure the validity of our data (S3 in the Supporting Information). Because of the shallowness of such peaks, the difference between the initial or peak onset and the final data point was not great and the sigmoidal line was roughly linear. It can be seen that the GLAD-MACE sample has a weaker signal than that of SA2. The pore peak position of the GLAD-MACE sample is 267 °C, which is very close to that of sample SA2 at 268.5 °C. Note that the signal from the TPM experiment of the IL-MACE sample was so weak that the heat-flow curve looks flattened in Figure 6. Using the set of α and δ values obtained from the TPM experiments from microparticles, we carried out calculations based on eqs 1 to 9 and obtained the pore parameters for the GLAD-MACE and IL-MACE nanowire samples. Figure 7 shows plots of PSD versus Rp for the GLAD-MACE and ILMACE nanowire samples. It can be seen that the GLADMACE nanowires have a PSD mostly distributed between 5 and 15 nm with nanowires a dominating pore diameter of ∼6 to 7 nm. The PSD of the IL-MACE nanowires, however, shows a nearly flat distribution from ∼5 nm onward. This flat distribution is most likely due to the non-well-resolved heat flow data for this type of sample. Table 3 lists the values of Rp, VDSC, and ADSC obtained from the TPM data of GLAD-MACE and IL-MACE samples. First, there seems to be little difference in the values of Rp, VDSC, and ADSC for GLAD-MACE and IL-MACE nanowire samples obtained from z = 2 or 3. Note that the Rp value of the GLADMACE nanowires is in the range of 5.86 to 5.90 nm, which is close to that of samples FS2 and SA2. The ADSC and VDSC values of the GLAD-MACE wires are approximately 1 order of magnitude smaller than those of FS2 and SA2. This explains the
Figure 6. (A) Measured heat-flow curves for GLAD-MACE, ILMACE nanowire and SA2 samples. (B, C) Expanded views on the onset of the pore peaks for GLAD-MACE and IL-MACE nanowires, respectively. The peaks appear as a change in inflection point on the heat curve, and they overlap with the onset of the bulk melting peak at around 270 K.
weaker heat flow signal of the GLAD-MACE sample in Figure 6. The Rp value of the IL-MACE nanowires is 4 times that of GLAD-MACE, but the VDSC and ADSC values of the IL-MACE nanowires are more than 2 orders of magnitude smaller than FS2 and SA2. This explains the almost flattened heating curve of the IL-MACE sample in Figure 6B. We mentioned earlier in the Experiments section that the GLAD-MACE nanowires were thinner and more porous than the IL-MACE nanowires on the basis of the SEM and TEM results. Our TPM results in Table 3 confirm that the GLAD2212
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sample. There is also an ∼50-fold increase in ADSC for the GLAD-MACE sample than for the IL-MACE sample. It is encouraging to note that our TPM results of the GLADMACE and IL-MACE nanowires compare favorably with the BET results of Hochbaum et al. on porous and nonporous nanowires.12 The BET experiments of Hochbaum et al. yielded a mean surface area of 342 m2/g and a total pore volume of 0.88 cm3/g for the porous nanowires. This surface area corresponds to an equivalent area of 490 m2/g for porous silica resulting from the difference in density. The corresponding mean surface area and total pore volume of our GLAD-MACE samples are 51.24−54.30 m2/g and 0.078−0.087 mL/g, respectively. Although these numbers are in a similar range to that reported by Hochbaum et al., it probably accounts for our difficulty in performing BET experiments on our samples. The different values of pore volume and surface area obtained between the nanowires in this work and in Hochbaum et al. may be due to the different catalysts (Ag vs Au) and method used in preparing catalysts (solution based for AgNO3 and solid state for Au). However, it is interesting that the pore distribution curve of Hochbaum et al. also showed a very similar distribution to that in our Figure 7A. The surface area of the nonporous control nanowires of Hochbaum et al. is 1 order of magnitude greater than for our IL-MACE sample (c.f. 24 to 0.91−0.93 m2/g), again indicating the difficulty in carrying out TPM experiments on the IL-MACE samples. Note that the pore distribution curve of the nonporous control nanowires also showed a flattened curve. In our previous work,9 we aminated both the GLAD-MACE and IL-MACE nanowire-based devices using 3-aminopropyltriethoxysilane (APTES), and the density of the reactive amine groups was examined by direct coupling to Cy5-NHS esters. We reported that a flat Si surface (i.e., the control sample) was found to display minimal fluorescence, indicating very low Cy5NHS coupling. The IL-MACE nanowire device exhibited a 40fold increase in Cy5-NHS coupling over that of the flat Si surface. In contrast, a significantly greater amount of Cy5-NHS coupling (∼500-fold higher) compared to that for the flat Si surface was observed on GLAD-MACE nanowire device. We have estimated that for a smooth IL-MACE nanowire a 2.5-fold increase in the surface area would be expected as compared to that for the flat Si substrate. However, the 40-fold increase in the coupling efficiency of Cy5-NHS to the IL-MACE nanowire device indicates that a simple estimation based on an increase in the substrate surface area alone cannot account for the observed increase in the coupling efficiency on the IL-MACE nanowire device. Table 3 shows that the Rp of the IL-MACE sample is ∼4 times larger than that of the GLAD-MACE sample, and this difference in Rp is unlikely to account for increases of 40- to 500-fold for Cy-5-NHS coupling to the IL-MACE and GLADMACE nanowire-based devices, respectively. We have seen from our thermoporometry results in Table 3 that there is an increase of approximately ∼50-fold in the values of ADSC and VDSC of the GLAD-MACE nanowire sample over the IL-MACE nanowire sample. This is in very good agreement with our earlier report of a 1 order of magnitude increase in the Cy5NHS coupling between these two types of devices.9 Therefore, we suggest that the improved performance of the GLADMACE nanowire device is due to the increase in the total pore surface area and volume of the nanowires.
Figure 7. (A) Pore size distribution of two GLAD-MACE samples and one IL-MACE nanowire samples calculated from TPM data obtained at a heating rate of 5 °C/min. (B) Enlarged view of the IL-MACE nanowire PSD.
Table 3. Calculated Values of the Pore Diameter (Rp), Total Pore Volume (VDSC), and Total Pore Surface Area (ADSC) of GLAD-MACE and IL-MACE Nanowires GLAD-MACE Rp (nm) VDSC (mL/g) ADSC (m2/g)
IL-MACE nanowires
z=2
z=3
z=2
z=3
5.86 0.087 54.30
5.90 0.078 51.24
20.48 0.0085 0.93
23.07 0.0084 0.91
MACE nanowires have a smaller pore diameter than the ILMACE nanowires, and the number of pores per unit mass is much higher in the GLAD-MACE nanowires than in the ILMACE sample. This is in good agreement with our SEM and TEM results in that the TEM image showed a much rougher surface for the GLAD-MACE sample than for the IL-MACE 2213
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(5) Gupta, V. K.; Saleh, T. A. Sorption of pollutants by porous carbon, carbon nanotubes and fullerene - an overview. Environ. Sci. Pollut. Res. 2013, 20, 2828−2843. (6) Mutreja, I.; Kumar, D.; Boyd, A. R.; Meenan, B. J. Titania nanotube porosity controls dissolution rate of sputter deposited calcium phosphate (CaP) thin film coatings. RSC Adv. 20, 28, 11263− 11273. (7) Tao, A.; Franklin, K.; Hess, C.; Goldberger, J.; Rongrui, H.; Yugang, S.; Xia, Y.; Yang, P. Langmuir-Blodgett silver nanowire monolayers for molecular sensing using surface-enhanced Raman spectroscopy. Nano Lett. 2003, 3, 1229−1233. (8) Horvath, E.; Ribic, P. R.; Hashemi, F.; Forro, L.; Magrez, A. Dye metachromasy on titanate nanowires: sensing humidity with reversible molecular dimerization. J. Mater. Chem. 2012, 22, 8778−8784. (9) Dawood, M. K.; Zhou, L.; Zheng, H.; Cheng, H.; Wan, G.; Rajagopalan, R.; Too, H. P.; Choi, W. K. Nanostructured Si-nanowire microarrays for enhanced-performance bioanalytics. Lab Chip 2012, 12, 5016−5024. (10) Kim, J. K.; Cho, J. Spinel Li4Ti5O12 nanowires for high-rate Liion intercalation electrode. Electrochem. Solid-State Lett. 2007, 10, A81−A84. (11) Ranjusha, A.; Nair, S.; Ramakrishna, S.; Anjali, P.; Sujith, K.; Subramanian, K. R.V.; Sivakumar, N.; Kim, T. N.; Nair, S.r V.; Balakrishnana, A. Ultra fine MnO2 nanowire based high performance thin film rechargeable electrodes: effect of surface morphology, electrolytes and concentrations. J. Mater. Chem. 2012, 22, 20465− 20471. (12) Hochbaum, A. I.; Gargas, D.; Hwang, Y. J.; Yang, P. Single crystalline mesoporous silicon nanowires. Nano Lett. 2009, 9, 3550− 3554. (13) Brun, M.; Lallemand, A.; Quinson, J.-F.; Eyraud, C. A new method for the simultaneous determination of the size and shape of pores: the thermoporometry. Thermochim. Acta 1977, 21, 59−88. (14) Ishikiriyama, K.; Todoki, M.; Motomura, K. Pore size distribution (PSD) measurements of silica gels by means of differential scanning calorimetry. J. Colloid Interface Sci. 1995, 171, 92−102. (15) Quinson, J. F.; Astier, M.; Brun, M. Determination of surface areas by thermoporometry. Appl. Catal. 1987, 30, 123−130. (16) Riikonen, J.; Salonen, J.; Lehto, V.-P. Utilising thermoporometry to obtain new insights into nanostructured materials. J. Therm. Anal. Calorim. 2011, 105, 823−830. (17) Dawood, M. K.; Zheng, H.; Liew, T. H.; Leong, K. C.; Foo, Y. L.; Rajagopalan, R.; Khan, S. A.; Choi, W. K. Mimicking both petal and lotus effects on a single silicon substrate by tuning the wettability of nanostructured surfaces. Langmuir 2011, 27, 4126−4133. (18) Choi, W. K.; Liew, T. H.; Dawood, M. K.; Smith, H. I.; Thompson, C. V.; Hong, M. H. Synthesis of silicon nanowires and nanofin arrays using interference lithography and catalytic etching. Nano Lett. 2008, 8, 3799−3802. (19) de Boor, J.; Geyer, N.; Wittemann, J. V.; Gosele, U.; Schmidt, V. Sub-100 nm silicon nanowires by laser interference lithography and metal-assisted etching. Nanotechnology 2010, 21, 095302−1−095302− 5. (20) Fukusako, S. Thermophysical properties of ice, snow, and sea ice. Int. J. Thermophys. 1990, 11, 353−372. (21) Jähnert, S.; Vaca Chávez, F.; Schaumann, G. E.; Schreiber, A.; Schönhoff, M.; Findenegg, G. H. Melting and freezing of water in cylindrical silica nanopores. Phys. Chem. Chem. Phys. 2008, 10, 6039− 6051. (22) Moore, E. B.; de la Llave, E.; Welke, K.; Scherlis, D. A.; Molinero, V. Freezing, melting and structure of ice in a hydrophilic nanopore. Phys. Chem. Chem. Phys. 2010, 12, 4124−4134. (23) Angell, C. A. Amorphous water. Annu. Rev. Phys. Chem. 2004, 55, 559−583. (24) Faivre, C.; Bellet, D.; Dolino, G. Phase transitions of fluids confined in porous silicon: a differential calorimetry investigation. Eur. Phys. J. B 1999, 7, 19−36.
IV. CONCLUSIONS We reported the results of a systematic study of the porosity of microparticles and nanowires prepared by the GLAD-MACE and IL-MACE techniques using the TPM method. We demonstrated good agreement between our TPM-derived parameters and that provided by the manufacturers of microparticles. The α and δ values obtained from the TPM experiments of microparticles were then used for the TPM characterization of GLAD-MACE and IL-MACE nanowires. We found that the increase in the total pore volume and total surface area of the GLAD-MACE nanowires was the most likely reason for the enhanced bioanalytical performance of such a device.
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ASSOCIATED CONTENT
S Supporting Information *
Description of the iteration processes used to derive and fit parameters for thermoporometry data. This material is available free of charge via the Internet at http://pubs.acs.org.
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AUTHOR INFORMATION
Corresponding Author
*E-mail: [email protected]. Author Contributions
J.W. and H.Z. contributed equally to this work. Author Contributions
The manuscript was written through the contributions of all authors. All authors have given approval to the final version of the manuscript. Notes
The authors declare no competing financial interests.
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ACKNOWLEDGMENTS This work was supported by a grant from the Singapore-MIT Alliance and a Proof-of-Concept grant (R-263-000-047-001) from the National Research Foundation. We acknowledge Fuji Sylisia (Japan) for supplying the silica microspheres without charges. We also thank Professor Lee Jim Yang of the Department of Chemical and Biomolecular Engineering of NUS for useful discussions of our TPM results. J.W. thanks the NUS Graduate School for Integrative Sciences and Engineering for the provision of a research scholarship, H.Z. acknowledges the GLOBALFOUNDRIES Singapore Pte. Ltd and the Economic Development Board (EDB) of Singapore for providing a research scholarship, and H.C. acknowledges the Singapore-MIT Alliance for the provision of a research scholarship.
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REFERENCES
(1) Cai, K.; Lv, Z.; Chen, K.; Huang, L.; Wang, J.; Shao, F.; Wang, Y.; Han, H. Aqueous synthesis of porous platinum nanotubes at room temperature and their intrinsic peroxidase-like activity. Chem. Commun. 2013, 49, 6024−6026. (2) Liao, H.; Hou, Y. Liquid-phase templateless synthesis of Pt-onPd0.85Bi0.15 nanowires and PtPdBi porous nanoparticles with superior electrocatalytic activity. Chem. Mater. 2013, 25, 457−465. (3) Moutanabbir, O.; Isheim, D.; Blumtritt, H.; Senz, S.; Pippel, E.; Seidman, D. N. Colossal injection of catalyst atoms into silicon nanowires. Nature 2013, 496, 78−82. (4) Qiao, Y.; Li, C. M. Nanostructured catalysts in fuel cells. J. Mater. Chem. 2011, 21, 4027−4036. 2214
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(25) Hardy, S. C. A grain boundary groove measurement of the surface tension between ice and water. Philos. Mag. 1976, 35, 471− 484. (26) Landry, M. R. Thermoporometry by differential scanning calorimetry: experimental considerations and applications. Thermochim. Acta 2005, 433, 27−50.
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